Package weka.classifiers.bayes

Class Summary

AODE	AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence less detrimental) independence assumptions than naive Bayes.
AODEsr	AODEsr augments AODE with Subsumption Resolution.AODEsr detects specializations between two attribute values at classification time and deletes the generalization attribute value. For more information, see: Fei Zheng, Geoffrey I.
BayesianLogisticRegression	Implements Bayesian Logistic Regression for both Gaussian and Laplace Priors. For more information, see Alexander Genkin, David D.
BayesNet	Bayes Network learning using various search algorithms and quality measures. Base class for a Bayes Network classifier.
ComplementNaiveBayes	Class for building and using a Complement class Naive Bayes classifier. For more information see, Jason D.
DMNBtext	Class for building and using a Discriminative Multinomial Naive Bayes classifier.
HNB	Contructs Hidden Naive Bayes classification model with high classification accuracy and AUC. For more information refer to: H.
NaiveBayes	Class for a Naive Bayes classifier using estimator classes.
NaiveBayesMultinomial	Class for building and using a multinomial Naive Bayes classifier.
NaiveBayesMultinomialUpdateable	Class for building and using a multinomial Naive Bayes classifier.
NaiveBayesSimple	Class for building and using a simple Naive Bayes classifier.Numeric attributes are modelled by a normal distribution. For more information, see Richard Duda, Peter Hart (1973).
NaiveBayesUpdateable	Class for a Naive Bayes classifier using estimator classes.
WAODE	WAODE contructs the model called Weightily Averaged One-Dependence Estimators. For more information, see L.